reduced order modeling of floating offshore wind · pdf filereduced order modeling of...

Stuttgart Wind Energy @ Institute of Aircraft Design
Reduced Order Modeling of Floating Offshore Wind Turbines
2nd International Summer School on Stochastic Dynamics of Wind Turbines and Wave Energy Absorbers August, 6th - 8th, 2014
Aalborg University
Frank Sandner, Stuttgart Wind Energy (SWE) University of Stuttgart/Germany

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Stuttgart Wind Energy (SWE)
Measurement & Control: Preview control Wind field
reconstruction Conceptual Design & Simulation: Floating Wind
coupled simulations, CFD, model tests
Validation with measurements (Alpha Ventus)
[Floatgen]
[SWE, InnWind.EU] [SWE,Simpack]
[SWE, NREL] [USTUTT,IAG]

Stuttgart Wind Energy @ Institute of Aircraft Design
Acknowledgements
The use and re-distribution of the slides is only allowed upon request to the author.
These slides are partly based on work by Denis Matha, Steffen Raach and David Schlipf. Their contribution is greatly appreciated.

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Whats in this lecture?
To get an understanding of the Floating Wind Turbine (FOWT) as a dynamic system and its modeling techniques.
To get an idea of how to select the appropriate model simplification.
To set up a first coupled model.

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Outline
1. How to numerically model a Floating Offshore Wind Turbine (FOWT)?
2. Model Applications
3. How to reduce/simplify the model?
4. Example: MBS FOWT model Structural model: Newton-Euler Equations Aerodynamic model Hydrodynamic model
5. Reduced model applications
6. Conclusions and Takeaways
[Ideol]

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How to model a FOWT (in general)? (1)

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How to model a FOWT (in general)? (2)
Model features:
Coupled/uncoupled Static/dynamic Linear/nonlinear Steady/transient Time/frequency domain Frequency range DOFs, involved modes 2D/3D Parametrizable Computational effort/speed
(real-time?)

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How to model a FOWT (in general)? (3) Limited overview on existing software/packages/coupled models:
FAST (NREL) FAST+ORCAFLEX (Orcina) FAST+MLTSIM (Technip) FAST+OPASS (Cener) FAST+UOU (U of Ulsan)
GH-Bladed (DNV-GL) SIMO-RIFLEX-HAWC2 (DNV-GL, DTU) SIMPACK+HydroDyn
(Dassault Systmes, USTUTT, NREL) 3DFloat (UMB) HydroGAST (NTUA) WAMSIM (DHI) SWT (LMS-Samcef) DeepLinesWT (Principia) CAST (U of Tokyo) Wavec2Wire (WaveEC)
Cordle, A., & Jonkman, J. (2011). State of the Art in Floating Wind Turbine Design Tools. In 21st International Offshore and Polar Engineering Conference.
Code2code comparison: Robertson, A., Jonkman, J., & Musial, W. (2013).
Offshore Code Comparison Collaboration , Continuation: Phase II Results of a Floating Semisubmersible Wind System. In Proceedings of the EWEA Offshore. Frankfurt.
Robertson, A., Jonkman, J., Vorpahl, F., Popko, W., Qvist, J., Froyd, L., Heege, A. (2014). Offshore Code Comparison Collaboration Continuation Within Iea Wind Task 30: Phase Ii Results Regarding A Floating Semisubmersible Wind System. In Proceedings of the ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. San Francisco, USA.

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Model Applications (1)
Overview on model applications
Why do we need reduced/simplified models?

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1. Conceptual design: Early stage coupled simulations Parametric studies Fast load simulations
[Ideol]
DLC
Wind Conditions Wave Conditions
Events PSF Model Wind Speed Model Wave Height Direction
1.x Power Production
1.1 NTM Vin < VHub < VOut NSS Hs = E[Hs | VHub] = 0 Normal operation 1.25 1.2
1.3 ETM Vin < VHub < VOut NSS Hs = E[Hs | VHub] = 0 Normal operation 1.35
1.4 ECD Vhub=Vr+/- 2m/s, Vout NSS Hs = E[Hs | VHub] = 0 Normal operation 1.35
1.5 EWS Vin < VHub < VOut NSS Hs = E[Hs | VHub] = 0 Normal operation 1.35
1.6a NTM Vin < VHub < VOut ESS Hs = 1.09 Hs50 = 0 Normal operation 1.35
2.x Power production plus occurrence of fault
2.1 NTM Vhub=Vr , VOut NSS Hs = E[Hs | VHub] = 0 Pitch runaway 1.35
2.3 EOG Vhub=Vr+/- 2m/s, VOut NSS Hs = E[Hs | VHub] = 0 Loss of load 1.1
6.x Parked (standing still or idling)
6.1a EWM VHub = 0.95 V50 ESS Hs = 1.09 Hs50 = 0, 30 Yaw = 0, 8 1.35
6.2a* EWM VHub = 0.95 V50 ESS Hs = 1.09 Hs50 = 0, 30 -180 < Yaw < 180 1.1
6.3a EWM VHub = 0.95 V1 ESS Hs = 1.09 Hs1 = 0, 30 Yaw = 0, 20 1.35
7.x Parked and fault condition
7.1a EWM VHub = 0.95 V1 ESS Hs = 1.09 Hs1 = 0, 30 Yaw = 0, 8
1 seized blade 1.1

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1. Conceptual design: Early stage coupled dynamic simulations Parametric studies Fast load simulations
2. Study/understanding of system dynamics:

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Turbulent wind Still sea vs. irregular sea
Motion Loads

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2. Study/understanding of system dynamics: Controller design Mass dampers Subsystem adaptation (mooring lines,
secondary elements)
[Stewart 2012]

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2. Study/understanding of system dynamics: Controller design Mass dampers Subsystem adaptation
(mooring lines, secondary elements) 3. Real-time model:
Software-in-the-loop experiments (Cener, Polimi, UMaine)
Model-based control, optimal control
past
predicted disturbance
predicted system
reference
future
projected control
horizon [Schlipf 2013]

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Model Applications: Summary
Questions to be answered by the model:
1. System dynamics or component dynamics (specific effect)?
2. Coupled or uncoupled dynamics?
3. Type of analysis: Steady states, modal, or frequency reponse?
4. Outputs: Displacements, sectional loads, stresses
5. Postprocessing: Min/Max/Mean/Stdev, etc.
Constraints:
1. Availability of data
2. Computational speed
3. Parametrization, batch mode
4. Flexibility of the software, availability of the code

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How to reduce the FOWT model? (1)
Structural Model:
EMBS
Elastic Multibody system (EMBS) Elastic parts: full FEM or reduced
MBS
MBS of rigid bodies Spring-damper couplings
Reduction
Modal reduction, CMS (e.g. Craig Bampton Method)
Krylov subspace, SVD

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EMBS reduction: Project the equations of motion into a smaller space.
Modal approximation: Spatial loads not considered. Guyan reduction (condensation): Separation of
Master (external, interface) and Slave (internal, node displacement) coordinates.
Component mode synthesis (CMS): Identification of component modes. Homogeneous and particular solution to the EQM correction modes.
Krylov subspace methods: Large sparse systems, TF estimation
Singular value decomposition (SVD): Energy consideration, identification of system invariants.
traditional techniques
modern techniques
Nowakowski, C., Fehr, J., Fischer, M., & Eberhard, P. (2012). Model Order Reduction in Elastic Multibody Systems using the Floating Frame of Reference Formulation. In MATHMOD. Retrieved from http://seth.asc.tuwien.ac.at/proc12/full_paper/Contribution475.pdf
Stru
ctur
al d
ynam
ics

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Ab = 0.9969 -0.0030 0.0008 -0.0007 -0.0000 -0.0018 0.9801 0.0105 -0.0090 -0.0005 -0.0005 0.0013 0.9899 0.0177 0.0009 -0.0002 0.0058 -0.0162 0.8036 -0.0241 -0.0000 -0.0005 -0.0005 0.0033 0.9913
Singular-value decomposition (SVD):
Bb = -0.1445 -0.0246 -0.0537 0.0488 -0.0090 -0.0175 -0.0008 -0.0165 -0.0011 0.0001
Cb = -0.1466 -0.0725 0.0192 -0.0162 -0.0009
A2 B2
C2
[Lecture Notes Kenn Oldham, Umich ME562 2010]
Stru
ctur
al d
ynam
ics

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Gyroscopic effect? Frequency range?
(selection of modes) Extreme or fatigue
loads?
Stru
ctur
al d
ynam
ics
[SWE, Simpack]

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Aerodynamic Model:
CFD
Potential flow
BEM
Actuator point
Model features: Flow model:
Blade-tower interaction (wake calculation) Blade-vortex interaction Tip loss, dynamic stall, turbulent wake state Unsteady aerodynamics, dynamic inflow, 3D effects
Wind field model: Turbulence model 3D/2D/1D
Blade elasticity (also structural model): Flapwise Edgewise Twist

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[Buelk12]
[IAG]
[Wind Energy Handbook]
Aer
odyn
amic
s
3 2
,1
2
p
a rel
cM R v
CFD Lifting line & free wake vortex method
A

reduced order modeling of floating offshore wind · pdf filereduced order modeling of...

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